Upstarts Keep Data Warehousing Competitive

Vendor consolidation may be the rule in many IT categories, but data warehousing is proving to be an exception. That much is clear as The Data Warehousing Institute (TDWI) World Conference gets underway in Las Vegas this week with a flurry of announcements from upstart vendors.

Taken individually, the headlines aren't earth shattering: Aster Data has improved support for in-database analytic processing; Kognitio has landed GroupM as a major new customer; ParAccel has partnered with Fusion-io to support flash-memory-supercharged processing; Vertica has upgraded its query workload and resource management features. But taken together, the announcements underscore that the data warehousing universe is expanding, with alternative providers getting stronger despite the pressures of a weak global economy.

Competition has been stable at the top of the data warehousing market for years, with Teradata, Oracle and IBM once again topping the "leaders' quadrant" in the latest Gartner Magic Quadrant (MQ) report for data warehousing, released earlier this month. Microsoft and Sybase are in the leaders' quadrant, too, but the upstarts are hoping to follow in the footsteps of Netezza. The only alternative provider that has made it into the top-right corner of Gartner's report, Netezza has used the combination of competitive pricing and fast query performance to win more than 300 customers to date.

Growth in data warehousing is being fueled by the so-called "big-data era." With Web sites, enterprise applications and networks cranking out data by the terabytes per day (and sometimes per hour), it seems there's more than enough room for up-and-coming vendors promising high performance and petabyte-level scalability at a lower cost -- at least compared to what Teradata, Oracle or IBM might charge.

Aster Data, among the newest additions to Gartner's MQ, today announced Aster Data nCluster 4.5, an upgrade of its core product featuring a combined SQL/MapReduce visual development environment, a suite of prebuilt analytics modules, support for Fusion-io flash-memory drives, and a new management console for optimizing query performance.

Popularlized by Google, MapReduce has quickly become the default choice for many kinds of data transformations and analytic processes while SQL remains the prevailing query language. Aster Data isn't the only vendor to support MapReduce -- Greenplum and Cloudera also support the approach -- but by offering a unified, visual environment for both SQL and MapReduce development, Aster is hoping to win over the many firms that combine the two approaches.

Aster Data's calling card is in-database analytic processing, an increasingly popular approach that speeds processing by running applications next to the data rather than extracting data and processing in the application environment. Teradata and Netezza have led the way in making in-database processing a reality, but Gartner says Aster's four-tier architecture is particularly well suited to the approach.

Citing the example of an online gaming site, Aster Data says it helped the customer move a java-based risk-analysis application inside nCluster for faster and more complete analysis.

"It used to take them 90 minutes to do the analysis on a subset of the data," says Sharmila Mulligan, executive vice president of global marketing at Aster Data. "The app now runs every 15 minutes against the entire data set, and it returns results within 90 seconds."

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